Learning to Resolve Social Dilemmas: A Survey (Abstract Reprint)

Social dilemmasare situations of inter-dependent decision making in which individualrationality can lead to outcomes with poor social qualities. The ubiquity of social dilem-mas in social, biological, and computational systems has generated substantial researchacross these diverse disciplines into the study of mechanisms for avoiding deficient outcomes by promoting and maintaining mutual cooperation. Much of this research is focused on studying how individuals faced with a dilemma can learn to cooperate by adapting their behaviours according to their past experience. In particular, three types of learning approaches have been studied: evolutionary game-theoretic learning, reinforcement learning, and best-response learning. This article is a comprehensive integrated survey of these learning approaches in the context of dilemma games. We formally introduce dilemma games and their inherent challenges. We then outline the three learning approaches and, for eachapproach, provide a survey of the solutions proposed for dilemma resolution. Finally, we provide a comparative summary and discuss directions in which further research is needed.